Radon Exposure and Risk of Leukemia: A Protocol of Systematic Review and Meta-Analysis

Abstract

Introduction: Radon is a naturally occurring radioactive gas that is considered a risk factor for many health problems, including leukemia. Although there are many scientific studies on this relationship, the available evidence is still inconclusive. This review and meta-analysis aims to provide a comprehensive overview of the existing literature to provide a more in-depth understanding of the relationship between radon exposure and leukemia risk.

Methods: A comprehensive search of large electronic databases was conducted to identify studies on the association between radon exposure and leukemia. Inclusion criteria were used to select epidemiological studies reporting primary data on this association. Qualitative evaluation is conducted throughout the design process and data extraction is performed independently by two researchers. In meta-analyses, a random-effects model was used to calculate overall results, and subgroup analyzes were performed to investigate sources of variability.

Results: The systematic review identified several studies that met the inclusion criteria. Meta-analyses show overall effect sizes and confidence intervals that indicate the nature of the relationship between radon and leukemia. To investigate sources of heterogeneity, cluster analysis was performed based on relevant factors such as study design and geographic location. A sensitivity analysis was performed to assess the robustness of the findings and assess potential reporting bias.

Conclusion: The systematic review identified several studies that met the inclusion criteria. Meta-analyses showing overall effect sizes and confidence intervals illustrate the nature of the relationship between radon and leukemia. To investigate sources of heterogeneity, cluster analysis was performed based on relevant factors such as study design and geographic location. A sensitivity analysis was performed to evaluate the effectiveness of the study results and assess the potential for publication bias.